Keyword Indexing for Backup Search Optimization

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Solution Overview

Problem

Existing data protection systems face challenges in efficiently indexing and searching large volumes of backup data due to the high storage costs associated with full content indexing, which limits the adoption of keyword searches.

Innovation Solution

A balanced approach is adopted by creating lists of 'optimal' keywords and scraping or extracting terms from files and backups, then storing only the listed terms that match the optimal keywords for subsequent text searches, utilizing machine learning to identify frequently and globally searched keywords.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If full content indexing is implemented to enable keyword searches, then search capability is improved, but storage space consumption increases prohibitively

Engineering Contradiction:

Improvekeyword search capabilityVSAvoidstorage space

Core Design Contradiction:

Ease of operationVSQuantity of substance

Solution Approach 1:

The patent extracts only the most frequently searched keywords from the full content of backups and stores them in an index, rather than indexing all content. This selective extraction enables keyword searches while dramatically reducing the storage space required for the index compared to full content indexing.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

Instead of implementing complete full-content indexing, the patent applies partial indexing by selecting and indexing only a subset of keywords that are most likely to be searched. This partial action provides sufficient search capability for common queries while avoiding the prohibitive storage costs of indexing every word in every backup.

Inventive Principle:

Principle #16Partial or excessive action

2Quantity of substance

If metadata-only indexing is used to reduce storage costs, then storage efficiency is improved, but keyword search capability is lost

Engineering Contradiction:

Improvestorage spaceVSAvoidkeyword search capability

Core Design Contradiction:

Quantity of substanceVSEase of operation

Solution Approach 1:

The patent implements a middle ground between metadata-only and full-content indexing by partially indexing selected keywords from the content. This provides keyword search capability for the most important terms while maintaining storage efficiency, avoiding both extremes of complete metadata indexing (insufficient search capability) and complete full-content indexing (excessive storage consumption).

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS12332751B1Identifying keywords for indexing content and searching backups

Publication Date: 2025.06.17 DELL PROD LP

AI summary

A system identifies a list of frequently identified keywords, which are identified based on frequencies that each frequently identified keyword is in any backup document and frequencies that any backup document contains each frequently identified keyword. The system identifies a list of locally searched keywords, which a data protection system used for searching local backups. A machine learning model creates a ranked list of globally searched keywords, which multiple data protection systems used for searching global backups, wherein each globally searched keyword is weighted based on use in global searches that resulted in any keyword match and/or any backup restore. The system identifies terms from backups which match keywords from the frequently identified keywords, the locally searched keywords, and/or the globally searched keywords. The system enables content searches, based on indexing the matched terms, of the backups.